1. Field
Apparatuses and methods consistent with exemplary embodiments relate to encoding and decoding of a binary image.
2. Description of the Related Art
Since each symbol (i.e., bit) of a binary image has a value of “0” or “1,” it is difficult to apply a conversion-based compression method or a prediction-based compression method to the binary image. Thus, a lossless compression method that uses binary arithmetic coding (BAC) is mainly used to encode the binary image without employing a prediction process in a related art. Examples of the lossless compression method used to encode the binary image include modified Huffman (MH), modified READ (MR), modified modified READ (MMR), Joint Bi-level Image Experts group (JBIG), and the like. The MH and MMR are encoding algorithms applied to G3 and G4 facsimile machines. The JBIG compression is a context-based arithmetic coding algorithm.
A BAC algorithm such as the related art JBIG compression is used to perform context-based coding in order to enhance compression performance. Context refers to a condition of symbols near a current symbol. The related art JBIG generates context of the current symbol by applying a template having invariable size and shape. Furthermore, JBIG2, which is an extension of the related art JBIG compression, increases arithmetic operation complexity in calculating context by increasing the size of the template.